Data Warehouse Sizing Calculator

237 KB | 3 files | null DOC,null XLS,null PDF

Since Data Warehouses are optimized for quick and simple reporting, picking the right size for the warehouse is a key component of making the project pay off. This simple calculator will help with that task.

A data warehouse is a specialized database that is optimized for analysis, reporting and decision support at both the tactical and strategic levels. Data warehouses make sense because the data in production systems -- such as ERP systems — is stored and managed in ways that make analysis difficult. Creating new reports is therefore a time-consuming process that requires highly trained programmers who know how and where to access the required data. In contrast, with a data warehouse the process of creating new reports is relatively quick and easy, and can be done by department-level users with no need to involve the IT department. Sometimes the content of a data warehouse is partitioned by function into department-specific databases, often referred to as "data marts."

This Data Warehouse Sizing Calculator helps you estimate the memory size required for a data warehousing project involving data from as many as 5 business units, each with as many as 5 relevant DBs, and each DB with as many as 10 relevant fields.

The process for using this calculator is as follows:

Step 1: Determine which business units will be contributing data.

Step 2: Identify which DBs controlled by that business unit have relevant data.

Step 3: Within each DB, identify the relevant rows.

Step 4: Determine the average length (number of characters) in each of these rows.

Step 5: Enter the data.

The attached Zip file includes:

  • Intro Page.doc
  • Cover Sheet and Terms.pdf
  • Data Warehouse Sizing Calculator.xls
IT Downloads help you save time and money while executing essential IT management tasks. Download this useful resource now and put it to work for your business.
Related IT Downloads

Analytics7 Big Data: Storage, Sharing, and Security

Chapter 2 focuses on answering questions faced by individuals interested in using storage or database technologies to solve their Big Data problems. ...  More >>

DataM33 Digital Exhaust: What Everyone Should Know About Big Data, Digitization and Digitally Driven Innovation

In this excerpt, Neef focuses on doing business in the Big Data world, including the scope of projects already underway, the primary drivers behind initiatives, and how Big Data is changing both the organization and c-level leadership roles. ...  More >>

HealthCare01 Big Data and Health Analytics

The chapter excerpt focuses on how effective data architecture must lay out the life cycle of data, from definition to capture, storage, management, integration, distribution, and analysis. ...  More >>

Subscribe Daily Edge Newsletters

Sign up now and get the best business technology insights direct to your inbox.